@InProceedings{FloresJúniorMCCLCNB:2019:AsSaAl,
author = "Flores J{\'u}nior, Rog{\'e}rio and Maciel, Daniel Andrade and
Cairo, Carolline Tressmann and Carlos, Felipe Menino and Lobo,
Felipe de Lucia and Carvalho, Lino Augusto Sander de and Novo,
Evlyn M{\'a}rcia Le{\~a}o de Moraes and Barbosa, Cl{\'a}udio
Clemente Faria",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Universidade Federal do Rio de Janeiro (UFRJ)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Assessment of satellite algorithms for deriving chlorophyll-a from
turbid waters of Amazon floodplain lakes",
booktitle = "Anais...",
year = "2019",
editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco
and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
pages = "1938--1941",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "Water quality, Chlorophyll-a, Empirical algorithms, Remote
sensing, Landsat, Sentinel.",
abstract = "The Amazon floodplain represents one of the most important
terrestrial ecosystems being a highly complex and dynamic
environment, with a key role in the global carbon cycle.
Therefore, the monitoring and management of their aquatic systems
is vital to increase the knowledge on the biogeochemistry
involving water components. Optically Active Components (OACs) as
chlorophyll-a (chl-a) can be a proxy to environmental parameters
such as water trophic status and primary productivity. Standard
methods to determine chl-a are based on in situ measurements being
expensive and time consuming, alternatively, remote sensing can be
a viable option through the calibration of chl-a algorithms.
Therefore, this work aims the assessment of empirical algorithms
for chl-a retrieval in Amazon lakes with turbid waters using
Remote Sensing reflectance (Rrs) from in situ data gathered in
four campaigns between 2015 and 2017. In situ Rrs was then used to
simulate Landsat 8/OLI and Sentinel 2/MSI images which were
calibrated and validated by Monte Carlo simulation. The best
algorithms were validated using images acquired almost
concurrently to in situ data acquisition for both sensors.
Preliminary results pointed out the ability to estimate chl-a with
errors smaller than 30% for MAPE for simulated data.",
conference-location = "Santos",
conference-year = "14-17 abril 2019",
isbn = "978-85-17-00097-3",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3UA4L38",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3UA4L38",
targetfile = "97890.pdf",
type = "Sensoriamento remoto de {\'a}guas interiores",
urlaccessdate = "25 abr. 2024"
}